If there’s one thing marketers have learned over the years, it’s this: never get too comfortable with Google.

Every few years, an algorithm update drops like a surprise pop quiz. Panda punished thin content, Penguin cracked down on spammy links, and Hummingbird made everyone suddenly care about “semantic search.” Each time, SEO pros scrambled to decode what it meant, rewrite their playbooks, and calm their clients.

But this time, it’s different.

The rise of AI-driven search and shopping isn’t just another algorithm tweak; it’s a full-blown revolution. Artificial intelligence is changing how people search, where they search, what they click (or don’t click), and how they buy. AI Overviews, large language models (LLMs), and new AI-driven shopping tools are reshaping the organic landscape faster than you can say “page rank.”

In short: Google’s updates used to shake up your keyword rankings.
Now, AI innovation is shaking up the entire idea of organic traffic.

The question every marketer is now asking: what happens when Google stops being your biggest traffic driver?

The Decline of Traditional Click-Through Experiences

If your organic traffic graph lately looks like a ski slope, you’re not alone.

According to SEMrush, AI-driven search could overtake traditional engines as the preferred search method by 2028. And we’re already seeing the ripple effects of this. Google’s AI Overviews, launched in 2024 as part of its Search Generative Experience (SGE), now appear in roughly 13% of queries, more than double what we saw from January to March 2025.

The result? Nearly 60% of all searches now end without a single click. Some industries are seeing traffic declines as steep as 15% to 64% since AI Overviews rolled out. Publishers, eCommerce sites, and SaaS companies are feeling it the hardest.
That means even when you’ve done everything “right”, optimized your content, targeted the perfect keywords, and snagged a top position, users might get their answer straight from Google’s shiny AI summary instead of visiting your site, and you’ll never reap the rewards.

In short: you’re still the brain behind the answer, but the robot gets the credit.

The Rise of LLM Search

If that all sounds a little bleak, here’s the silver lining: overall there are some signs suggesting that AI-referral traffic may be higher quality than traditional.

Visitors coming from LLMs like ChatGPT, Claude, or Gemini are proving to be high-intent power users. Data from SEMRush shows that LLM-driven visitors are 4.4 times more likely to convert than those arriving from traditional search.

Adobe’s 2024 holiday retail analysis backs this up: visitors from AI-driven search stayed 8% longer, viewed 12% more pages, and bounced 23% less than their Google-born counterparts.

And the growth? Astronomical. Between July 2024 and February 2025, AI-driven traffic to retail websites jumped 12x, outperforming traditional sources in engagement across the board.

Think of it this way: traditional SEO was about ranking. LLM search is about relevance. The AI doesn’t care about backlinks—it cares about useful answers. And if your brand delivers those, you’re in the game.

AI As a Sales Channel

Until recently, AI-powered interactions were all about discovery: product recommendations, personalized search results, and maybe a chatbot helping users find the right pair of sneakers. But now, artificial intelligence isn’t just influencing shopping decisions, it’s completing them.

Nearly a third of consumers have already used some kind of AI interface to make a purchase. Whether it’s asking a digital assistant for “the best noise-canceling headphones under $200,” or letting a smart mirror recommend a shade of lipstick, shoppers are starting to trust machines with their buying decisions. And the more intuitive these experiences get, the more that trust turns into transactions.

The biggest shake-up so far? ChatGPT’s instant checkout feature.
It’s still new, and the data’s early, but its potential is enormous. Imagine a shopper typing, “What’s a good moisturizer for sensitive skin?” and ChatGPT not only recommends your product, but lets them hit ‘Buy Now’ right there in the chat. No tabs, no scrolls, no bouncing between apps. Just a single, seamless conversation from curiosity to conversion.

For marketers, that’s both thrilling and a little terrifying. Traditional eCommerce funnels, the carefully crafted journeys from awareness to decision, are collapsing into a single AI-powered moment. Discovery, evaluation, and purchase now happen in one interface, guided by algorithms trained on millions of data points and conversations.

This shift builds an entirely new sales ecosystem, where the “storefront” might not even belong to you. The future of selling isn’t just about ranking high on Google or optimizing your PDPs. It’s about being present, trusted, and purchasable wherever the conversation happens, whether that’s on ChatGPT, Perplexity, Gemini, or whatever AI assistant your next customer decides to befriend.

How to Adapt to the Future of AI Commerce

If all this talk about AI eating your traffic and rewriting the sales funnel has you sweating—don’t. This isn’t the end of organic discovery; it’s just the start of a smarter, more dynamic version of it.

The brands that thrive in this new era won’t be the ones clinging to keyword rankings or chasing every algorithm tweak. They’ll be the ones structuring their data, refining their product stories, and meeting customers (and machines) exactly where they are.

Here’s how to future-proof your visibility and make sure your brand stays discoverable even when the next click never comes.

1. Understand how LLMs currently understand your business

Before you can optimize your visibility in AI-driven search, you first need to know what these models think you do. Large language models like ChatGPT, Gemini, and Claude are essentially well-read students; they’ve consumed massive amounts of information about your industry, your products, and your competitors. But whether they actually understand your brand correctly? That’s another story.

This is where tools like Akeneo’s AI Discovery Optimization feature come in, which helps businesses enrich, structure, and present product information in ways that align with how LLMs interpret and retrieve data. Instead of chasing the right keyword density or backlinks, the goal now is to make your content machine-comprehensible. The better an AI model understands your catalog, your values, and your differentiators, the more likely it is to include you in responses—or even recommend you outright.

Think of it as SEO for the AI age. Clarity, structure, and semantic richness replace keyword stuffing and meta tag tinkering. Your job isn’t to trick algorithms anymore—it’s to teach them who you are.

2. Incorporate customer feedback & insights into your product language

If you want to know how AI describes your brand, don’t look at your website – look at your customers. A recent study revealed that Reddit, Quora, and LinkedIn are among the most-cited sources in Google’s AI Overviews. Translation? AI is literally learning how to talk about your products from what real people are saying about them online.

The best way to stay relevant is to listen to those customer conversations and incorporate them into your product language. Use the same words, phrases, and problem statements your customers do. Reflect their tone and intent in your product descriptions, FAQs, and educational content. When your content mirrors authentic customer language, AI systems are more likely to cite you as a trusted, contextually relevant source.

3. Leverage structured and enriched data to increase AI discoverability

AI thrives on structured data. It’s how it decides what to trust. Use schema markup, comprehensive metadata, and enriched product attributes to make your content “machine-friendly.” The more context you give, the more likely AI systems are to understand (and cite) you accurately. When your product information is consistent, complete, and machine-readable, it’s far more likely to surface in AI Overviews, be cited in conversational answers, and even be recommended in emerging AI shopping tools.

4. Start tracking LLM referral traffic & other new KPIs to stay ahead

 As large language models like ChatGPT, Perplexity, Gemini, and Copilot start shaping more customer journeys, they’re quietly becoming meaningful sources of referral traffic. The catch? Most brands aren’t even tracking it yet. Start by looking for patterns in your analytics that hint at AI origins; unusual referral URLs, sudden spikes in direct traffic after trending topics, or visits that seem to appear out of thin air (spoiler: they probably came from an AI assistant). Some analytics platforms are already experimenting with dedicated tracking for AI-based referrals, and those who adopt early will gain a serious head start.

Beyond traffic, it’s time to expand your KPIs. Measure AI citation volume (how often your content is mentioned or quoted by AI tools), engagement depth (how long users stay after arriving from AI-powered sources), and AI-assisted conversions (purchases or sign-ups that began with an AI interaction).

Embracing the Future of Search & Shopping

Google may have been the sun around which your marketing universe once revolved, but that solar system is expanding fast. Now, discovery happens across an entire constellation of AI-driven platforms, assistants, and interfaces, all illuminating new pathways between curiosity and conversion.

Yes, that means the organic landscape is more complex than ever. But it’s also more exciting. For the first time, brands aren’t confined to search results. They can exist in conversations, recommendations, and even purchases that happen without a browser tab. The marketers who embrace this shift, who enrich their product data, listen to customer language, and understand how AI perceives their business, will be the ones who stay visible in the age of machine-mediated discovery.

Predicting the future is a tricky business. If we’d asked an expert in 2016 what shopping would look like today, they probably would’ve imagined drones dropping off Amazon boxes by the hour and smart fridges automatically restocking our oat milk.

Some of that’s happened (sort of), but the truth is, technology always surprises us, especially in eCommerce. Every year brings a new twist, and 2026 looks like it’s going to be one of the most fascinating yet.

That’s why we’re donning our futurist hats; not the shiny sci-fi kind, but the practical kind that marketers, retailers, and digital innovators wear when they try to spot what’s coming next. We’re analyzing real data, evolving consumer behavior, and the technologies already reshaping how we browse, buy, and engage in order to peer into the crystal ball and see what’s on the horizon. 

From AI-powered search tools that know your taste better than your best friend, to digital passports that tell the life story of your favorite products, here’s what’s about to redefine eCommerce as we head into 2026.

1. AI-powered product search & discovery

Traditional online search sometimes feels like shouting into the void. You type in a few keywords, cross your fingers, and hope the algorithm understands you. But for many shoppers, those days are over. The new era of eCommerce is powered by artificial intelligence that can actually infer and understand what you’re looking for, even when you don’t.

AI-driven discovery is already transforming how consumers browse, compare, and decide what to buy. 49% of Americans say AI recommendations already influence what they buy, and 64% of people say they’re willing to purchase items recommended by generative AI. SEMrush even predicts that AI-powered search will overtake traditional search as the preferred choice by 2028.

Visual search is also expected to keep gaining traction too, as consumers upload photos of something they saw on social media and find near-identical matches in seconds. Retailers are using these systems to personalize experiences in real time, learning from browsing behavior, preferences, and even mood signals to fine-tune recommendations.

2. The first step towards agentic commerce

We know—two AI trends in a row. But before your eyes glaze over, hear us out: if AI-driven search is about helping people find the right product, then large language model (LLM)-based purchasing is about helping them buy it without ever touching a checkout page.

LLMs like ChatGPT can now recommend products, compare features, and even complete purchases, all within a single chat. While this may sound futuristic, the adoption curve is already steep. A recent TechRadar report found that about one-third of U.S. consumers would let AI make purchases for them, and nearly a third have already used ChatGPT to assist in buying decisions.

Here’s how it might look in 2026: you tell your favorite AI assistant, “I need a gift for my dad—something under $100, and he loves gardening.” The assistant instantly pulls options from verified retailers, checks delivery dates, and finalizes the purchase, all while you sip your coffee. 

For brands, this opens a brand new sales channel. Of course, this shift also raises important questions about data privacy, consent, and how to maintain human connection when algorithms start handling transactions. But there’s no denying the momentum: AI may be helping us to shop today, but in the coming years, it will start to simply shop for us.

3. Increased supply chain transparency with Digital Product Passports

While AI tends to steal the headlines, another quietly revolutionary change is coming to eCommerce in 2026: the rise of the Digital Product Passport (DPP). Think of it as a digital birth certificate for every product, detailing where it was made, what it’s made of, and how it can be reused or recycled.

Driven by the European Union’s Ecodesign for Sustainable Products Regulation (ESPR), DPPs are set to become mandatory for certain product categories beginning in 2026 and 2027. These digital records will accompany items throughout their entire lifecycle, from raw materials to end-of-life, helping consumers make informed, sustainable choices.

For brands, this is both a compliance challenge and a storytelling opportunity. Consumers increasingly want to know the “why” behind what they buy; where it came from, who made it, and what impact it has. With DPP, a customer will be able to scan a QR code on a sweater and see its full history: which factory produced it, how much carbon it generated, and how to recycle or repair it later. 

By 2026, expect to see Digital Product Passports popping up across Europe and beyond. And once consumers get used to this level of visibility, there’s no going back.

See how Akeneo & Ocode can help you create Digital Product Passports.

4. Social commerce & user generated content (UGC)

Between 2023 and 2025, the number of social shoppers in the U.S. grew from roughly 96 million to 104 million. By 2026, those numbers will soar even higher, with TikTok alone projected to have nearly 40 million buyers in the U.S.

This growth isn’t surprising when you consider how people, especially younger audiences, discover products. Today, 43% of Gen Z consumers start their online shopping searches on TikTok, surpassing even Google and Amazon. Social media has become the new mall, where product discovery, community engagement, and purchasing all happen in one place.

User-generated content (UGC) also plays a massive role in this transformation. Shoppers trust people who look and talk like them more than polished brand campaigns. Reviews, unboxings, and “TikTok Made Me Buy It” videos are today’s word of mouth, and they convert at remarkable rates. Live shopping events, creator collaborations, and shoppable posts blur the line between entertainment and eCommerce, making shopping feel less transactional and more experiential.

By 2026, expect social commerce to become fully normalized. Platforms like Instagram, TikTok, and YouTube are continuing to refine in-app checkout options, allowing users to buy instantly without leaving their feeds. 

At the same time, brands are learning to co-create with their audiences, turning customers into advocates and content creators. The result? A more authentic, community-driven form of commerce, where a single viral video can sell out a product overnight.

5. A resurgence of hybrid shopping experiences

With all this talk about AI and digital transformation, you might think physical retail is dead. Spoiler alert: it’s not even close. In fact, hybrid shopping, where customers fluidly move between online and in-person touchpoints, has quickly become the norm.

Consumers still crave tangible experiences, and the data proves it. In a recent consumer survey we conducted here at Akeneo, we found that 75% of shoppers have bought something in-store after researching for it online, and 65% have done the opposite; purchasing a product online after browsing for it in a physical location.

In 2026, the most successful brands will be those that seamlessly blend the physical and digital worlds. Physical stores are already starting to evolve into experiential hubs: places to see, touch, and interact with products, to attend brand events, or even to process online returns with ease.

With so many advancements with the online shopping journey, it’s important to ask what’s driving this in-person surge? While consumers believe that algorithms can predict their preferences, they can’t fully replace the satisfaction of walking out of a store with your purchase in hand. For many consumers, that tactile joy will always matter. The smartest retailers aren’t choosing between physical and digital, but are designing ecosystems that make both shine.

How to Prepare for 2026 

Predicting the future of eCommerce may always involve a bit of educated guesswork, but one thing is certain: every major trend on the horizon depends on one thing above all else: great product data.

AI can’t recommend the right product if the underlying information is incomplete. Digital Product Passports can’t deliver transparency if product data is scattered across systems. Social commerce doesn’t work if your product descriptions, visuals, and attributes aren’t optimized for each channel. And hybrid experiences crumble without a unified, accurate source of truth about your products.

In 2026, success will belong to the brands that build a solid data foundation first. Reliable, enriched, and structured product information is what turns innovation into impact.

So while no one can perfectly predict what’s next in eCommerce, we can prepare for it. The future may be powered by AI and automation, but it runs on something far more fundamental: trustworthy product data. Get that right, and whatever the next big thing turns out to be, you’ll already be ahead of the curve.

Since the introduction of the world wide web, there have been a couple evolutions in eCommerce that stick out as key historical moments; Amazon breaking on to the scene in the late 90s to sell all products A to Z, the introduction of Cyber Monday to encourage online holiday shopping, and the eCommerce boom that came from quarantined consumers during the pandemic, to name a few.

Now it’s time to add a new one to the list: OpenAI’s new “Instant Checkout” feature.

For the first time, discovery, trust, and purchase can all happen seamlessly within a single conversation. There are no new tabs to open, no carts to abandon, no competitor websites to double check that you’re getting the best deal, and no friction between consideration and conversion. 

When the discovery channel itself becomes the point of purchase, the rules of engagement change entirely. For businesses that have long relied on traditional SEO strategies, paid digital ads, and organic traffic to attract customers, OpenAI’s latest announcement means that every dollar spent chasing success with Google’s everchanging algorithm, every hour spent optimizing metadata, and every campaign built around driving clicks to a website risks becoming wasted effort if that website is no longer where buying decisions happen.

The traditional pathways to purchase are being rewritten in real time, and if you aren’t prepared to ride this next wave of eCommerce evolution, you risk being left behind in the wake.

How to Prepare for OpenAI’s Instant Checkout

This is a new frontier of discovery and purchase, and as LLMs like ChatGPT change and evolve over time, we’ll gain a clearer understanding of how they interpret intent, prioritize responses, and decide which brands or products to surface within a conversation.

But what’s already clear is this: AI agents require contextualized, enriched, and accurate product information. Unlike traditional search engines that reward keyword optimization, these new systems rely on richly detailed and well-structured data to make meaningful connections between a shopper’s query and a brand’s offering. 

That means that success no longer depends on who can outsmart an algorithm, but on who can provide the most complete, consistent, and contextualized information within a data ecosystem that AI can actually understand and trust.

It also means that businesses need to be able to create a “closed loop” between product data and the LLMs themselves in order to ensure continuous refinement. In this loop, brands provide consistent, enriched, and contextualized data, and in return, they can learn how that data is being interpreted and presented to customers. 

Building that loop is just one piece of the puzzle. To truly prepare for this next wave of eCommerce, businesses will need to rethink how they manage, enrich, and connect their product information across every channel. 

That’s why the team here at Akeneo has identified five essential capabilities that all businesses need to embrace in order to ensure their product data is ready for agentic commerce.

1. Understand how you’re currently being interpreted

You can’t optimize what you don’t understand. If you don’t know how your products are being represented inside an LLM (or how your customers are actually talking about them), you’re effectively flying blind. 

PX Insights helps you see exactly how your products and brand are being talked about across AI-powered experiences and customer channels. By capturing real-life reviews, ratings, and feedback, you gain a complete picture of how your products are being discovered (or missed), and can then refine your data accordingly.  

This means that you’re not just optimizing for today’s models like ChatGPT, but for whatever is to come next. With PX Insights, you can learn from your product data, and close the loop between how your products are presented and how they actually perform.

 The good news? For existing Akeneo customers, PX Insights is available through a one-month free trial, offering a risk-free way to see how insights-driven optimization can transform your product experience strategy.

2. Ensure your product data is discoverable

Yesterday, being “ready” meant being SEO-compliant. Today, it means being GEO-compliant — optimized for Generative AI Engines. As we mentioned earlier, this means your product data needs to be rich enough, structured enough, and accurate enough for AI to understand and recommend it confidently.

Akeneo’s Data Architect Agent makes that possible by helping you design scalable, intelligent data models in minutes, drastically reducing the time and effort usually required to structure and standardize your product catalog. It ensures your data model isn’t just functional, but future-ready, giving your products the foundation they need to be discoverable across both traditional and AI-driven channels.

Ask yourself: do your products include every attribute a shopper needs to make a buying decision? Are your descriptions, specs, and images aligned with what customers actually search for and care about? Is your product data structured clearly enough for AI models to understand and surface it confidently? Are you able to adapt your product data in real time as customer preferences and LLMs evolve?

Only when your product data meets that level of completeness, clarity, and adaptability can your products be truly discoverable in this new era of agentic commerce.

It’s also important to point out that Shopify is already one of the first platforms compatible with ChatGPT’s latest feature. That means if your Shopify store is powered by Akeneo, you’re already in an incredibly strong position. Akeneo ensures your product data in Shopify is clean, complete, and consistent across every attribute, image, and description. When that enriched data flows into ChatGPT’s instant checkout experience, your products are surfaced accurately and compellingly, helping shoppers buy faster and with confidence. 

In short, by getting your product data right in Shopify — powered by Akeneo — you can optimize this powerful new AI-driven channel even faster.

3. Utilize the full power of your existing assets

Your product content is more powerful than you think. Assets like images, spec sheets, lifestyle videos, and installation guides are data-rich resources that can drive conversions when utilized effectively. But all too often, these assets sit idle, disconnected from the product experience they’re meant to enhance. 

With Akeneo, you can extract structured information from assets like PDFs or high-resolution imagery to automatically populate product attributes, saving time, reducing manual effort, and improving accuracy.

The result? Richer, more consistent product experiences that not only builds shopper confidence but also makes your data more legible to AI agents.

4. Tailor GenAI enrichment to your brand voice

Generic prompts create generic results. In a marketplace where differentiation is everything, your brand voice can’t be left to chance. Akeneo’s AI configuration panel gives you full control over how generative AI represents your brand, from tone and style to values and vocabulary.

You can design, test, and refine AI prompts that reflect your brand’s unique character, ensuring every product description, headline, or translation feels authentically you. With brand-aligned AI enrichment, you can deliver content that’s not only faster, but unmistakably on-brand.

5. Maintain human expertise in the loop

AI alone isn’t enough; the most successful brands know that automation should empower, not replace, their teams. With Akeneo’s built-in workflows, AI-generated content moves through human review and approval before publication, combining the efficiency of automation with the discernment of human judgment.

This approach safeguards accuracy, creativity, and compliance while dramatically shortening time to market. By keeping experts in the loop, you preserve brand integrity and product quality, turning AI into a trusted collaborator, not a black box.

Preparing for the Next Wave of eCommerce

Every major shift in eCommerce has redefined what it means to compete. From the dawn of online marketplaces to the rise of mobile shopping and social commerce, each transformation rewarded the brands that adapted fastest. 

OpenAI’s “Instant Checkout” marks the next evolution, where discovery and purchase no longer live on separate steps of the buyer journey but converge in a single, AI-driven moment of decision.

At Akeneo, we believe brands that thrive in the age of agentic commerce will be those that build stronger connections between their product information and the intelligent systems interpreting it. With tools like PX Insights, AI Discovery Optimization, and Data Architect Agent, you can close the loop between how your products are represented and how they’re discovered, ensuring your brand is not only visible today, but prepared for whatever comes next.

Not sure where to even begin? You can take our PX Maturity Assessment to give you a clear view of your strengths and the areas to prioritize first. 

Whether you’re launching your first PIM project or scaling a global ecosystem, we’re ready to meet you wherever you are. The future of commerce won’t wait, but readiness doesn’t mean rebuilding everything overnight. 

With Akeneo Product Cloud, you can turn product data into your strongest competitive advantage: complete, enriched, consistent, and ready to shine in every new channel, including ChatGPT. The rules of commerce may be changing, but with the right foundation, your brand can not only keep up, but lead.

Do you remember the first time your favorite local coffee shop greeted you by name and started making your usual order before you even asked? That moment felt like exceptional service—but really, it was your first taste of a truly personalized experience.

Today, that same expectation extends far beyond your morning coffee. Consumers don’t want generic messages or one-size-fits-all offers; they expect brands to understand their preferences and anticipate their needs. In fact, our survey found that two in five consumers would pay up to 25% more for a personalized shopping experience.

What Does “Personalized Experience” Mean?

A personalized experience is any brand interaction that feels intentionally made for an individual customer — based on who they are, what they do, and what they need. Rather than pushing the same products or messaging to everyone, these experiences adjust in real time using customer insights like past purchases, browsing habits, location, or even customer service interactions. This kind of authentic connection makes customers feel recognized and helps deliver a high-quality product experience that builds trust from discovery to post-purchase.

Different Types Of Personalized Experiences

Personalization takes many forms. And each plays a unique role in shaping how individual customers engage with your brand:

1. Product Recommendations: Helping Customers Find What They Didn’t Know They Needed

Product recommendations are one of the most recognizable and impactful forms of personalized customer experience. Whether it’s the classic “Customers also bought” row or a curated homepage based on your browsing behavior, these dynamic suggestions help guide customers toward relevant products and services they may not have discovered otherwise. 

What makes this approach so powerful is its ability to connect customers with offerings that align with their tastes and needs, without having them do the searching themselves. This not only improves product discovery and shortens the path to purchase, but also increases basket size and satisfaction, making customers feel like the brand gets them. For many businesses, product recommendations are a major driver of both loyalty and margin, turning a basic browsing session into a high-value customer interaction rooted in personalization.

How AI Powers This:

Artificial Intelligence (AI) and Machine Learning (ML) sit at the core of modern recommendation engines. These technologies analyze a combination of real-time customer behavior (such as time spent on pages and cart activity) and historical data like past purchases, product ratings, or even abandoned items. By continuously learning from this data, AI models can predict what an individual customer is likely to want next and surface it instantly, whether that’s through the homepage or a Product Detail Page (PDP).

And AI is doing more than just improving the checkout experience; 49% of shoppers say AI-powered recommendations have influenced their purchase decisions. And with ChatGPT’s recent announcement of their “Instant Checkout” feature that allows consumers to purchase products directly within the AI interface, we can only expect this percentage to grow.

2. Personalized Messaging: Speaking to the Right Customer at the Right Time

Forget mass email campaigns! Today’s customers expect messaging that’s timely and customized to their individual preferences. Personalized messaging, whether through email, SMS, push notifications, or social media, enables brands to speak directly to each customer with content that reflects their interests and position in the purchase journey. From abandoned cart nudges to restock alerts, every touchpoint becomes an opportunity to deepen engagement and drive retention. When personalization efforts are thoughtful and well-timed, they feel like a natural part of the shopping experience. And as customers navigate an expanding landscape of channels and interactions, contextual messaging is essential for delivering a unified and seamless brand experience.

How AI Powers This:

Delivering that level of personalization across multiple touchpoints isn’t easy, especially at scale. That’s where AI makes the difference, helping brands move beyond static segments to build dynamic messaging strategies that respond to customer behavior. With the ability to generate tailored content and adapt on the fly, AI ensures communication stays relevant and contextual. Tools like Akeneo PX Insights play a key role in making this possible by leveraging behavior data to inform smarter decisions within your Product Information Management (PIM). The solution empowers teams to optimize messaging and product content based on how customers actually interact across channels. And by uncovering not just what customers engage with, but why, brands can deliver smarter product experiences grounded in real insights.

AI’s role in performance optimization becomes even more impactful when applied to customer communication. Take Amazon, for example — their AI-powered personalization strategy has transformed how they engage customers through email. By analyzing individual behavior, purchase history, and preferences, Amazon’s machine learning algorithms generate hyper-personalized email content tailored to each recipient. Suppose a customer recently purchased a book by a particular author. In that case, they might receive a follow-up email recommending other titles by the same or similar authors, all automatically curated by AI. This level of intelligent automation drives higher open rates and helps brands maintain consistent, high-value interactions over time.

3. Intuitive Browsing: Making Discovery Feel Effortless

One of the most underrated forms of personalization is how a customer navigates your digital storefront. Intuitive browsing is about making it easy (even enjoyable!) for customers to find what they’re looking for, or better yet, stumble across something they didn’t know they needed. This involves more than good UX design; it’s about adapting the interface, filters, categories, and search results to match the behavior and preferences of each customer. 

A returning visitor might see their favorite categories featured prominently, while a new shopper might be guided through a curated onboarding experience. The goal is to remove friction from the exploration phase of the customer journey and turn it into a satisfying experience that keeps people engaged and encourages repeat visits.

How AI Powers This:

This same intelligence extends beyond messaging, shaping how customers explore and discover products. AI plays a key role in making digital browsing feel more intuitive by adapting interfaces in real time based on user behavior and context. Rather than relying on fixed categories or keyword-matching alone, AI-powered systems use ML and Natural language processing (NLP) to interpret what a customer really means — not just what they type.

Take a search for “lightweight winter jacket.” A traditional search engine might simply pull every item containing those keywords in the title or description. In contrast, AI can analyze customer reviews to identify jackets most often praised for warmth without bulk, recognize which styles perform best in colder climates, and even factor in recent weather trends to promote products that align with real conditions. This level of intelligence helps deliver results that match intent instead of just wording, offering more meaningful and accurate recommendations.

Beyond search results, AI also reshapes the broader browsing experience, adjusting navigation menus and reorganizing category layouts to reflect real-time preferences. Brands like Sephora are already leading the way: after noticing a rise in detailed product searches, they used AI to generate landing pages tailored to queries like “best foundation for sensitive skin.” This not only delivered hyper-relevant content to curious shoppers but also led to a 6% boost in organic search visibility. It’s a perfect example of how AI can power both a smoother browsing journey and smarter product discovery, all while driving measurable results.

Personalization Starts with the Right Foundation

Great personalized experiences can only exist because of great data. No matter how sophisticated your AI or how creative your messaging, if the underlying product information is inconsistent or outdated, the experience falls flat. Today’s customers expect detailed product content, and when they get it, they’re more likely to convert and stay satisfied. In fact, 62% of consumers say they’re far more likely to keep a product and feel good about their purchase when the information they received was comprehensive and correct. 

Conversely, poor data drives up return rates and eats into margins. And in 2025, nearly a third of consumers reported dissatisfaction with the depth of product information they received, highlighting a growing gap between expectations and reality.

That’s why investing in tools like a PIM is essential. A modern PIM helps centralize product content, ensure consistency across all channels, and scale personalization efforts with confidence. Paired with enrichment capabilities powered by AI, brands can go beyond accuracy and start tailoring experiences for individual shoppers — delivering the right message, with the right information, at exactly the right moment. 

And the stakes are high: 77% of shoppers say they would abandon a site and look elsewhere if product details, pricing, or specifications were incomplete. This kind of content-driven personalization not only improves conversions but also reduces costly returns and preserves customer loyalty. 

The Power of Getting Personal — with Precision

Personalized experiences are grounded in great product data. Without complete, consistent, and context-rich information, even the smartest AI can’t deliver relevance or drive the kind of engagement today’s customers expect! From search to messaging to browsing, every touchpoint depends on the accuracy and depth of your product content.

When the product experience matches the product promise, everyone wins. With the right data foundation in place, supported by tools like PIM and enriched by AI, personalization becomes the best thing a business could have:  a sustainable growth strategy.

The year 2026 is shaping up to be a turning point for global commerce. The rise of AI-powered experiences and rapidly evolving customer expectations are transforming how businesses operate and compete. Our survey found that two-fifths of consumers would pay about 25% more for a personalized or tailored shopping experience, showing just how important data-led interactions have become.

At the same time, new sustainability and compliance regulations — including the Digital Product Passport (DPP) initiative in Europe — are raising the bar for transparency and traceability. Customers now expect consistent, reliable product experiences across every touchpoint, while organizations must manage complex data ecosystems, coordinate with suppliers, and stay agile in the face of growing regulatory demands.

In this fast-changing environment, Product Information Management (PIM) can act as the foundation for digital transformation, empowering businesses to manage and activate product information with greater efficiency and control. By allowing teams to align around a single source of truth and by streamlining how data flows across the organization, a modern PIM built on an API-first architecture enables smooth data exchange, faster integrations, and the flexibility to scale as your business grows.

As we move toward 2026, let’s look at the biggest challenges businesses will face — and how PIM can help solve them!

How PIM Can Solve Businesses’ Problems in 2026

To stay competitive in 2026 and beyond, businesses must overcome several critical data and operational challenges. Here’s how PIM plays a key role in tackling them:

1. Fragmented and Inconsistent Product Data

Disorganized and scattered product data remains one of the biggest barriers to business growth. Many organizations still rely on disconnected systems, from ERPs and spreadsheets to eCommerce platforms and DAMs, which leads to duplication and wasted time. These silos make it nearly impossible to deliver accurate and consistent product information across channels, hurting customer trust and operational efficiency. As regulatory and consumer expectations for data accuracy continue to rise, fragmented product information poses an increasingly costly risk.

PIM solves this by serving as a central hub for all product information, a single source of truth that unifies data from multiple systems. It provides a structured, governed environment where teams can enrich, validate, and distribute consistent product data across all channels. By ensuring that every stakeholder works from the same reliable foundation, businesses can eliminate redundancy and improve data accuracy well into 2026 and beyond.

2. Limited Readiness for AI and Data-Driven Experiences

AI-driven commerce is on the rise; in fact, SEMrush predicts that AI-powered search experiences will become the preference over traditional search methods by 2028. But here’s the secret: AI relies heavily on clean and enriched product data. Without it, recommendation engines, chatbots, and search algorithms deliver poor results, leading to missed opportunities and frustrated customers. Many organizations still struggle to prepare their data for these advanced use cases, limiting their ability to deliver personalized and predictive experiences.

PIM provides the data foundation needed for effective AI implementation. By ensuring product data is complete and standardized, PIM allows AI tools to perform at their best. This leads to more relevant search results, smarter recommendations, and improved automated content generation. With a reliable source of structured product information, businesses can confidently adopt AI technologies that enhance customer experience and operational efficiency.

3. Slow Product Launches and Time-to-Market Delays

Manual workflows, disconnected tools, and repeated data entry often slow down product launches, costing businesses valuable time in competitive markets. When teams across departments and regions work from different data sources, even minor updates require days or weeks of coordination. These inefficiencies not only delay launches but also limit the ability to respond quickly to changing market trends and consumer demands.

With PIM solutions, businesses can accelerate product launches through streamlined workflows, automation, and centralized collaboration. Teams can enrich data and approve changes within one unified platform, streamlining the journey from concept to launch. By improving visibility and eliminating duplicate work, PIM helps brands bring products to market faster — whether launching new lines or updating existing assortments.

Akeneo PIM takes this even further with tools designed to make the entire product launch process more intelligent and efficient. Its industry-centric product family templates simplify catalog modeling by preselecting the most relevant attributes for specific industries. Teams can automate repetitive tasks, from populating shared attributes and transforming data upon import to updating categories in bulk. The platform also pinpoints missing information and ensures that every product meets completeness and compliance standards before launch. With these capabilities, Akeneo PIM allows teams to focus on what matters most: enriching product data to create compelling experiences that drive conversions. It also helps businesses achieve a more scalable time-to-market.

4. Rising Sustainability and Compliance Expectations

As regulations like the Digital Product Passport (DPP) fully come into effect in 2026, businesses must prepare to manage both detailed and transparent product data. Customers and regulators alike expect visibility into sourcing, materials, recyclability, and carbon footprint. Essentially, all the information that is often scattered and difficult to maintain. Without a unified system, brands face compliance risks and reputational challenges.

A PIM solution centralizes and structures all product data in one place, making it easier to collect information from suppliers, enrich it with sustainability attributes, and standardize formats for compliance. Teams can capture critical environmental and social metrics with accuracy and confidence. By consolidating data into a single source of truth, businesses improve visibility across their supply chain and create a clearer product record that’s ready for DPP reporting.

With Akeneo PIM, businesses gain a future-proof foundation for sustainability and compliance management. It enables collaboration between marketing, product, and sustainability teams, ensuring everyone contributes to the same structured dataset. As regulations evolve, Akeneo PIM adapts. It allows brands to integrate with new DPP interfaces and scale across markets with ease. By providing a centralized structure for sustainability data, Akeneo PIM simplifies compliance and strengthens brand trust. It positions businesses as transparent, responsible leaders in the evolving landscape of 2026 and beyond!

5. Complex Multichannel and Omnichannel Management

A consistent and engaging product experience is now the expected standard for shoppers across every channel, from brand websites to online marketplaces. However, each channel comes with its own data structures, format requirements, and content rules, making it increasingly difficult for teams to manage product information manually. These challenges often lead to inconsistencies and inaccuracies that undermine brand trust and compromise the customer experience.

PIM simplifies this by enabling businesses to standardize and adapt information for every channel efficiently. Teams can easily update media and descriptions while maintaining a consistent brand voice and product story across regions and platforms. This streamlined approach ensures that every channel reflects accurate product content.

Beyond PIM, Akeneo Activation takes multichannel management even further by helping brands publish enriched product data directly to leading retailer and marketplace sites. Once a channel is enabled, required and optional attributes become visible within Akeneo, allowing teams to map existing PIM data to each destination’s specific requirements. Operations can also be configured to automatically transform PIM data to match each channel’s standards, eliminating repetitive manual work. This tight integration between Akeneo PIM and Akeneo Activation creates a powerful feedback loop, ensuring accurate data distribution and scalable automation across every digital touchpoint. The result is a cohesive, high-performing omnichannel experience that drives conversions and customer loyalty!

6. Poor Product Data Quality and Governance

Incomplete or inaccurate product data not only disrupts internal processes but also damages customer confidence. Inconsistent product naming and outdated content can lead to poor search performance, higher return rates, and (as you guessed it) lost sales. Without clear governance, maintaining data accuracy becomes increasingly difficult as product catalogs grow and evolve.

PIM provides built-in quality controls that ensure every product meets defined completeness and validation rules before publication. Its governance framework gives businesses visibility into data readiness and establishes accountability across teams. By maintaining high standards of product data quality, organizations can improve the customer experience and ensure long-term consistency as they scale globally.

7. Challenges in Global Expansion and Localization

Entering new markets requires accurate, culturally relevant, and compliant product information — a process that quickly becomes overwhelming without the right systems. Teams must manage multiple languages, currencies, measurement systems, and regional regulations, often juggling spreadsheets and manual translations. These inefficiencies not only slow expansion but also risk introducing inaccuracies that harm credibility with local consumers.

PIM simplifies global expansion by enabling businesses to manage multilingual and regional data in one centralized platform. Teams can easily localize content for each market while keeping it aligned with the central source of truth in PIM. The system’s flexible data model supports region-specific attributes, legal requirements, and brand messaging, empowering organizations to expand confidently into new markets while maintaining efficiency and brand integrity.

8. Inconsistent Supplier and Partner Data

Supplier data often arrives in multiple formats, varying levels of completeness, and inconsistent quality, forcing teams to spend countless hours cleaning and validating information. These errors create friction that delay product onboarding and disrupt the flow of accurate information throughout the organization.

PIM addresses this challenge by offering a structured environment where supplier data can be imported, validated, and enriched efficiently. It ensures that all information entering the system meets the organization’s data standards and can be seamlessly published to downstream channels.

To take this even further, Akeneo Supplier Data Manager (SDM) works hand in hand with Akeneo PIM, enabling suppliers to upload, correct, and enrich product data directly through a standardized interface. This collaboration centralizes supplier data collection and ensures consistency at the source by flagging errors in real time for immediate correction. By reducing manual intervention and streamlining product data normalization, businesses can onboard products faster and more accurately! This leads to a more efficient ecosystem where suppliers and internal teams work together to maintain high-quality, market-ready product data, all within Akeneo Product Cloud or as a standalone solution.

9. Siloed Collaboration and Inefficient Workflows

When teams rely on spreadsheets and manual updates, collaboration becomes slow and error-prone. Marketing, product, and eCommerce departments often work in isolation, duplicating efforts and losing visibility into the product data lifecycle. These silos lead to delays and miscommunication, which lead to missed opportunities to improve product experiences!

However, PIM eliminates silos by providing a shared workspace where teams can collaborate in real time. It guides teams through the enrichment process with defined roles, structured workflows, and task assignments, ensuring everyone knows their responsibilities and works toward shared goals. This not only streamlines processes and enhances productivity but also improves data consistency across departments, creating an aligned way of working.

Akeneo Shared Catalogs takes collaboration a step further by simplifying product data sharing and communication across teams and partners. Through a secure online product portal, sales and service teams, distributors, and retailers can access up-to-date and customized digital catalogs on demand — all synchronized automatically with Akeneo PIM. By enabling internal and external teams with real-time access to accurate product information, businesses can reduce time spent searching for data, bring products to market faster, and deliver richer customer experiences.

10. Lack Of Visibility into Product Content Performance

Many businesses publish product information without truly understanding how it performs across channels. Without visibility into content engagement or conversion impact, teams struggle to improve product storytelling and optimize data for customer needs.

PIM establishes the foundation for performance insight by ensuring high-quality product data across every channel. It allows teams to monitor completeness and ensure accuracy before publication.

When combined with Akeneo PX Insights and Akeneo Business Analytics, businesses gain a complete view of how product content drives engagement, conversions, and overall performance. PX Insights transforms customer behavior signals into actionable insights directly within Akeneo PIM. These insights help businesses refine content based on real customer interactions and boost visibility across channels. Meanwhile, Akeneo Business Analytics, built into Akeneo PIM, tracks key metrics such as sales, page views, and conversion rates to evaluate enrichment effectiveness and identify opportunities for optimization. Together, these tools provide the visibility needed to continuously refine product experiences and drive sustained omnichannel growth.

Preparing for 2026 and Beyond

As 2026 approaches, the ability to manage, trust, and activate product data will define which businesses thrive in the evolving digital landscape. Customer expectations and the rise of AI are transforming how brands must operate, and product information sits at the center of it all.

With Akeneo PIM and the broader Akeneo Product Cloud, organizations can build a single, scalable foundation for product data excellence. By breaking down silos, improving data quality, and unlocking insights across every channel, businesses can stay agile and customer-focused — ready to lead the next era of commerce with confidence.

The lines between online carts and shopping carts have never been blurrier, and that’s exactly how today’s consumers like it. One minute they’re comparing prices on their phones, the next they’re standing in an aisle scanning QR codes for reviews, and by evening, that same product shows up in their social feed with a “Still thinking about this?” nudge. 

Welcome to hybrid shopping, where convenience meets curiosity and the path to purchase weaves seamlessly between clicks and bricks.

As the 2025 holiday season approaches, the retail stage is set for another data-fueled shopping spectacle. While 51% of consumers plan to use online marketplaces, nearly half also intend to shop in-store at national and local retailers. The ability to navigate effortlessly between digital and physical touchpoints is the standard expectation for the modern holiday shopper

And behind this fluid experience? Artificial Intelligence. From smarter recommendations to predictive inventory, AI is the quiet driver behind hybrid shopping, helping brands meet customers wherever, whenever, and however they choose to shop. The question isn’t whether AI will change the way we shop, but how deeply it already has.

What Is Hybrid Shopping?

Hybrid shopping is the blend of online and in-store experiences, giving consumers the freedom to move naturally between eCommerce and brick-and-mortar channels. It provides consumers with the comfort of shopping online while enabling them to research or purchase those same products in brick-and-mortar stores. It’s not about choosing one channel over another, but about creating a consistent, flexible journey that fits how people actually shop today.

A shopper might browse online, test a product in-store, and complete the purchase through an app — or do it all in reverse! They might even choose options like Buy Online, Pick Up In Store (BOPIS) to pair digital ease with real-world speed. For brands, that agility demands connected product experiences across every touchpoint, a challenge increasingly powered and perfected by AI.

How AI Improves Hybrid Shopping

Artificial intelligence is transforming the hybrid shopping journey by bridging the gap between digital and in-store experiences. By analyzing data, predicting behavior, and personalizing interactions, AI empowers retailers to meet shoppers wherever they are, whether that’s online, in-app, or on the sales floor, with relevant, seamless experiences. 

Let’s take a look at five key ways AI enhances the hybrid shopping experience, helping brands create smarter, more connected, and more satisfying customer journeys.

1. Smarter Product Discovery

Finding the right product in a hybrid world shouldn’t feel like a treasure hunt. That’s where AI-powered visual and voice search steps in, making discovery faster and more intuitive. Instead of typing long or uncertain queries, shoppers can simply snap a photo, describe an item aloud, or use natural language to find what they’re looking for. IKEA’s app, for example, uses visual search to let customers take a picture of an item they like and instantly receive matching or complementary furniture suggestions. This turns inspiration into action by offering immediate, relevant results that mirror real-world intent.

Amazon’s app takes a similar approach with voice search, allowing users to tap the microphone icon and speak to look for products — no wake word or typing required. It’s a small but powerful example of how AI adapts to human behavior rather than the other way around. For hybrid shoppers moving between digital and physical worlds, these capabilities remove uncertainty and make product discovery feel more responsive.

2. More Tailored, Personalized Experiences

AI is redefining what personalization means in modern commerce. By analyzing browsing patterns, purchase history, and even subtle behavioral cues, intelligent systems can predict what shoppers want before they know it themselves. Sephora’s Virtual Artist app is a perfect example — it allows users to try on makeup virtually, but its real magic lies in how it recommends products! By understanding a shopper’s skin tone and preferences, the app suggests foundations and skincare products that feel tailor-made. It’s personalization that feels human, not because it replaces intuition, but because it enhances it.

Shoppers are clearly embracing this shift toward more interactive, tech-driven experiences. Between 40% and 45% of consumers say they’re interested in using AI-powered agents, voice assistants, or virtual reality (VR) tools to explore product features. Consumers want to experience products through immersive, intelligent tools that help them make smarter decisions. 

This depth of customization doesn’t just improve discovery; it influences buying decisions in powerful ways. Nearly half (49%) of shoppers say AI-powered recommendations directly impact what they purchase. Whether it’s curated product bundles or cross-sell suggestions, AI ensures that every interaction feels relevant, timely, and designed around real intent.

3. Faster Shopping with AI Checkout

ChatGPT’s new Instant Checkout transforms the hybrid shopping journey by collapsing discovery and purchase into a single conversational flow. When consumers ask ChatGPT for product recommendations, whether while browsing in-store via mobile, engaging via app, or just chatting at home, the system can display items that support Instant Checkout, allowing users to “buy” right there in the chat interface. No app switching, no redirecting to an eCommerce checkout page.

Consumers are ready for this kind of speed. Nearly a third (27%) have already used ChatGPT to make a purchase and said they would do it again, citing convenience and time savings as key advantages. Another 30% said they’d be open to trying AI-assisted checkout if brands clearly communicate how their data and payments are protected. 

In the context of hybrid retail, the rise of AI-powered commerce can blur the boundaries between offline and online touchpoints: a customer could be scanning items in a physical store, ask ChatGPT “which of these is the best deal,” and then buy the item via chat quicker than walking to the till. It also strengthens the value of conversational or voice interfaces as a real purchasing channel, rather than just a recommendation or comparison tool. That said, this shift also raises new challenges: brands may lose control over branded checkout experiences (upsells, cross-sells, branding), and managing trust, returns, and support becomes critical when AI intermediates the transaction.

4. Smarter Inventory and Supply Chain Management

AI is redefining how brands manage inventory and fulfill customer needs across both physical and digital channels – fundamental to delivering a seamless hybrid shopping experience. By analyzing real-time sales and operational data, AI enables retailers to anticipate demand more accurately, reducing waste and preventing stockouts whether shoppers are browsing online or visiting a store. This ensures that products are available where and when customers expect them, supporting consistent, convenient experiences across touchpoints.  A strong example comes from Unilever, the global CPG giant that uses AI to make its supply chain stronger as well as sustainable. Unilever leverages data-driven insights to proactively rethink how products are made, from sourcing new ingredients to refining formulas without losing quality.

Moreover, predictive analytics helps brands synchronize marketing, logistics, and merchandising in real time. By learning from search behavior, purchase trends, and local events, AI can help determine the best time to promote products, launch campaigns, or restock specific locations. The result is a connected ecosystem where every part of the business, from inventory management to customer engagement, works together to serve hybrid shoppers efficiently. In a world where online and offline retail are no longer separate, AI provides the intelligence needed to make every experience timely, relevant, and satisfying.

5. More Accurate, Reliable Product Data

Shoppers are increasingly discerning, and their trust hinges on the quality of information they see. When consumers can’t find the information they need, they leave. In fact, 77% of shoppers say they would abandon a site and look elsewhere if product details, pricing, or specifications were incomplete. In an era where research is rapid and comparison is effortless, missing or inconsistent information causes frustration and costs sales. 

AI plays a pivotal role in helping businesses deliver more reliable, consistent, and accurate product data, which is an essential ingredient in today’s hybrid shopping environment. By automatically detecting errors, filling in missing attributes, and standardizing data across multiple systems, AI ensures that product information remains consistent no matter where it appears. Machine learning models can analyze data from various sources like supplier catalogs, customer feedback, and online listings to identify discrepancies and improve accuracy at scale. This not only saves time for product and merchandising teams but also guarantees that shoppers see up-to-date, trustworthy information whether they’re browsing online or checking details in-store.

The impact on the hybrid shopping journey is huge. When customers encounter the same detailed, accurate information across touchpoints, they gain confidence in their purchase decisions. AI-powered enrichment tools can even personalize product data based on context, highlighting the most relevant attributes for each channel or customer type. By ensuring product data is both precise and contextually relevant, AI helps brands eliminate confusion, build trust, and create a unified, seamless experience from screen to shelf.

The Future of Hybrid Shopping Is Intelligent

As digital and physical retail continue to intertwine, one thing is clear: AI is enhancing and defining the hybrid shopping experience. From smarter discovery and personalized recommendations to seamless checkout and optimized inventory, AI empowers brands to meet shoppers where they are with precision and speed.

But AI can only be as powerful as the data behind it. Brands that invest in accurate, enriched product information will be the ones who stand out. With solutions like Akeneo PIM, part of the Akeneo Product Cloud, businesses can build the strong data foundation AI needs to thrive, creating meaningful product experiences that turn every interaction into an opportunity.

Once the Black Friday frenzy fades, a new wave of excitement takes over; Cyber Monday. What started as a clever marketing idea has evolved into one of the most powerful shopping days of the year, where deals drop faster than shoppers can click “add to cart.”

In 2024, consumers spent a staggering $13.3 billion on the major shopping event, with spending surging to nearly $15.8 million per minute at its peak! By the time Cyber Monday hits, shoppers are wide awake, credit cards at the ready, and expectations are higher than the discounts they’re chasing. If your brand isn’t seamless and trustworthy, your competitors will be more than happy to welcome those customers instead.

That may sound daunting, but here’s the good news: delivering a standout digital approach for Cyber Monday isn’t about shortcuts or assumptions. It comes down to combining accurate product data, smooth omnichannel execution, and more into a strategy that keeps your shoppers coming back.

Need more proof? Scroll down to see how you elevate your Cyber Monday game with Akeneo Product Cloud, tying it all together!

How to Create a Powerful Online Presence for Cyber Monday

A strong digital presence makes your products shine in a crowded marketplace while engaging shoppers at every touchpoint. Here’s how your brand can differentiate itself during the busiest shopping day of the year:

1. Leverage the Power of Personalization

Personalization is the main expectation on Cyber Monday. Shoppers want deals and recommendations that feel relevant to them, not one-size-fits-all discounts plastered across every channel. From curated bundles to specific offers, personalized experiences help consumers feel seen and understood, guiding them toward products they’re more likely to buy. In a shopping environment defined by urgency and competition, delivering this kind of individual relevance can be the key to capturing your customers’ attention and driving your conversions.

But that’s not all. AI has pushed personalization into an entirely new era. It’s not just about customizing the checkout process but instead about shaping what shoppers discover and ultimately purchase. Nearly half of consumers report that AI-powered recommendations influence their buying decisions, whether through suggested add-ons, complementary products, or limited-time offers based on browsing behavior. By anticipating shopper needs, AI helps brands shorten the path to purchase and increase average order value (AOV), all while creating a shopping journey that feels effortless.

Akeneo PX Insights elevates personalization by giving brands a smarter way to manage and optimize the data that powers it. AI streamlines the collection of product information from multiple sources and then organizes it into actionable data. This foundation allows brands to not only deliver accurate product experiences at scale but also refine them continuously. From boosting visibility across search and shopping platforms, PX Insights helps create more intelligent product experiences everywhere your customers shop!

2. Rethink Deal Days Beyond Discounts

Deal-day shopping now stretches across weeks, not hours. In fact, many retailers have expanded Black Friday and Cyber Monday into month-long events, with promotions kicking off as early as November 1st and running well into December. This extended window means Cyber Monday should be seen less as a single shopping day and more as the centerpiece of a broader holiday sales season,  one where timing and creativity make all the difference.

Shoppers also aren’t just chasing the deepest discounts. They’re looking for value, which blends price with product quality, convenience, and transparency. A one-dimensional strategy that relies only on slashing prices risks attracting bargain hunters who won’t return once the sale ends. By designing thoughtful deal-day campaigns, brands can score quick conversions now and plant the seeds of loyalty that last long after the wrapping paper is gone.

3. Deliver a Seamless Hybrid and Omnichannel Experience

Cyber Monday shopping has become increasingly channel-agnostic. Shoppers are no longer choosing between online and in-store — they’re doing both, often in the same buying journey. Research shows that while many consumers plan to shop on marketplaces like Amazon, nearly half also intend to visit national retailers or local brands in person. This means holiday shoppers expect a frictionless experience across all touchpoints: the same product information, pricing, and availability, whether they’re browsing your website or standing in-store.

For brands, this demand for consistency across channels is both a challenge and an opportunity. When shoppers move effortlessly between physical and digital experiences and receive consistent information throughout the journey, trust grows and conversions follow. On Cyber Monday, where decision-making happens fast, ensuring that product experiences are unified across channels is essential for capturing sales and keeping customers coming back.

This is where Akeneo Activation strengthens your omnichannel strategy by connecting enriched product data to leading retailers and marketplaces, ensuring content is always complete and optimized. It transforms PIM data into channel-ready formats automatically, reducing manual effort and freeing teams to focus on high-impact work. With continuously updated channel requirements and actionable insights, publishing stays seamless while customers enjoy compelling product experiences.

4. Provide Accurate and Transparent Product Information

Like every major shopping event, every detail counts. Shoppers moving quickly between retailers won’t waste time digging for missing specs or inconsistent descriptions. If the information shoppers need isn’t there, they’ll move on — usually straight to a competitor! And that’s the last thing you want on Cyber Monday. Accuracy removes doubt, allowing shoppers to commit to their purchase with confidence.

Today’s consumers are savvier than ever, often comparing products across multiple sites before deciding. Brands that present transparent and reliable information assure shoppers they’re making the right choice. From detailed specifications to clear delivery timelines, correct product data transforms uncertainty into trust and trust into conversions!

Akeneo PIM helps make that accuracy possible at scale. With a single source of truth for product information, teams can enrich, manage, and maintain high-quality product data across the business. And thanks to a diverse ecosystem and community of integrations, Akeneo PIM ensures enriched product content can be distributed efficiently across every channel, leading to coherent and memorable product experiences.

5. Provide Insight into Key Decision-Making Factors, Like Shipping Policies and Product Quality

When it comes to Cyber Monday, shoppers are calculating the best overall value. It’s a balance of price, quality, and how quickly (and cheaply) the product lands on their doorstep. A discount may catch their eye, but if shipping feels slow or costly, or if the product seems flimsy, the deal quickly loses its shine. For brands, this means making the total offer clear and attractive by highlighting competitive pricing, emphasizing delivery options that make buying simple, and offering flexible policies like easy exchanges or store credits.

Handled well, this balance positions a brand as delivering not just savings, but smart value. When customers move quickly between offers, clearly presenting price, quality, and fulfillment can be what wins the sale. Beyond the markdown, shoppers seek the assurance that what they’re buying is valuable and stress-free.

6. Build and Protect Brand Trust

On Cyber Monday, discounts may spark interest, but trust often seals the deal. Shoppers want to know that the brand behind the promotion is reliable and stands by its products. In fact, for 27% of consumers, credibility outweighs even the lowest price, determining if they go through with the purchase or move on to a brand that feels safer

Trust is built on continuity. Clear policies, dependable service, and honest communication reinforce for customers that what they see is what they’ll get. That certainty not only increases conversions in the heat of Cyber Monday but also lays the groundwork for long-term loyalty.

Built effectively, trust becomes a powerful competitive advantage that endures long after the holiday rush. Customers who feel confident in your brand during peak season are more likely to return, recommend, and remain loyal — even without a flashy discount!

Optimize With Akeneo Business Analytics and Shared Catalogs

Building a strong digital presence on Cyber Monday is only half the story. To sustain that momentum, brands need visibility into performance and the ability to share accurate product data seamlessly across teams and partners.

Oh, did someone call for Akeneo Business Analytics and Akeneo Shared Catalogs?

Having a clear view of performance metrics is key to knowing what’s working and what’s not. With Akeneo Business Analytics, brands can track everything from page views to conversion rates and revenue, all from one centralized dashboard. By connecting enrichment strategies directly to performance data, teams can see how product content drives engagement and sales across channels. These insights make it possible to enhance product experiences in real time and stay a step ahead of competitors during peak shopping periods.

And who said collaboration isn’t just as important? Instead of teams spending valuable time hunting for the right product information, Akeneo Shared Catalogs makes it simple to share up-to-date data through secure online portals that can be set up in minutes. Automated synchronization with Akeneo PIM ensures stakeholders always have the most current product information at their fingertips. Together, these two solutions enable faster time to market, streamlined operations, and consistency across every channel.

Winning Cyber Monday and Beyond

It’s pretty evident by now that Cyber Monday is more than just a day of deals. It’s a peak opportunity where brands prove their ability to deliver seamless and engaging digital experiences. From personalization and omnichannel consistency to accurate data, value-driven offers, and brand trust, success comes from balancing shopper expectations with operational excellence.

With the right tools and strategies in place, brands can stand out, convert shoppers, and earn loyalty that lasts well beyond the holiday rush. Cyber Monday may be the flashpoint, but the capabilities you sharpen now will strengthen your digital presence every day of the year.

Think it’s too early to be thinking about holiday shopping? Think again!

With major retailers rolling out Black Friday and Cyber Monday deals earlier every single year, and with 43% of consumers completing at least half of their holiday shopping during major deal day events like these, your brand is already late to the game if your haven’t at least started preparing for the holiday shopping season.

Not to worry; in the year of 2025, you have the power of technology on your side. The hype around AI has been hard to ignore, but the truth of how you can utilizing this powerful technology today lies somewhere between the diehard champions and the apocalyptic naysayers. 

To make the most of increased customer activity this holiday season, let’s take a look at eight tangible examples of how your brand can utilize AI technology to deliver an exceptional customer experience. And, to help demonstrate, we’ll be following along with fictional luxury jewelry brand Ziggany’s as they experiment with AI to give the gift of a better experience to their customers. 

1. Cleanse your data for accuracy & missing values

Before you can dive headfirst into the holiday shopping frenzy, take a moment to clean and organize your data. AI algorithms rely on data to make informed decisions; inaccurate or incomplete product data renders the whole purpose of implementing an AI solution useless.

To cleanse data effectively, you need to create and employ a combination of validation, standardization, and transformation techniques to ensure data accuracy, consistency, and completeness, while also implementing ongoing monitoring and governance practices to maintain data quality over time.

You can even use AI to clean your data before implementing AI solutions; I know, it’s a bit meta. But machine learning algorithms can automatically highlight data points that don’t fit the usual patterns, making it easier to find these errors, missing data, or inconsistencies.

In practice, this means that fictitious jeweler Ziggany’s can implement AI-driven data validation and cleansing tools to automatically review their product catalog, customer data, and inventory records ahead of the holiday season. If there are discrepancies in gemstone details or metal types, AI can flag these issues for review and correction.

Ziggany’s can also automatically identify and merge duplicate records in the customer database, preventing the same customer from being counted multiple times and ensuring accurate customer analytics with a machine learning algorithm before launching the holiday promotional campaign.

2. Embrace LLMs as a new discovery channel

AI can be super helpful behind the scenes, but with the recently announced “Instant Checkout” feature released by ChatGPT, it’s also impacting the way customers search, discover, and shop.

Instead of clicking through multiple product pages or comparing listings across retailers, consumers can now discover, evaluate, and purchase products directly within conversational AI interfaces.

For brands, this creates a powerful new opportunity: AI as a shopping destination. Instead of relying solely on traditional search engines or marketplaces, brands can integrate their product catalogs into AI ecosystems, enabling products to appear contextually within natural conversations.

Luxury jewelry brand Ziggany’s, for instance, could connect its product data to AI discovery channels so that when users chat about “sustainable fine jewelry” or “heirloom-worthy gifts,” their offerings appear organically within the conversation.

With enriched and structured product data, AI can not only identify relevance but also communicate detailed product attributes, things like materials, craftsmanship, ethical sourcing, and pricing, to create a richer, more persuasive experience than a static product listing ever could.

3. Improve site search functionality

The introduction of AI-powered shopping channels doesn’t mean you should just abandon your eCommerce storefront. If you’re looking to enhance your web presence this holiday season, AI-powered solutions can provide you with improved product tagging and categorization functionality, meaning that your customers can find the products they’re looking for on your site faster and easier.

For example, our friends at Ziggany’s probably internally label all products gemstone type with a long SKU identifier number ( e.g., “diamond” = 3426663, “sapphire” = 72774473). A properly trained machine learning algorithm can translate those jumbles of numbers to identifiable terms that a customer would come to your site and actually search for; then, it could extract these attributes like carat weight, metal purity, or gemstone cute to create detailed filters for the customers. 

Even if your customer comes to your site and searches “elegant diamond necklace” or “vintage sapphire ring”, natural language processing (NLP)-powered AI can understand these queries and ensure accurate search results even if the specific product name isn’t used.

4. Unburden your support team with live chat and intelligent routing

The holiday rush often means a surge in customer inquiries. One of the most popular implementations of AI is chatbots that can reduce the workload on your support team and improve the efficiency of your ticketing wiring system. These bots can handle routine questions, provide product information, and even intelligently route complex inquiries to human agents when needed.

For Ziggany’s, this could look like deploying AI-driven chatbots to handle common customer inquiries about ring sizing or fixing an unreliable bracelet clasps. These chatbots can also intelligently route complex queries to their expert support team for personalized assistance.

A properly trained AI solution could also ingest years of returns and support requests data, and provide Ziggany’s support team with an intelligent prediction of popular holiday items that tend to have fit or quality issues, and how to proactively address those issues.

5. Translate & localize product content

Today’s economy is an increasingly global one, and while eCommerce may open up doors to international markets, it also means that your product content needs to be able to be seen in different cultural contexts. Even small things, like “color” vs. “colour” in the U.S. and U.K., can interfere with search functionality and customer experience as much as major things, like including the appropriate unit of measure.

AI can play a pivotal role in translating and localizing product content for luxury jewelry brand Ziggany’s, ensuring a seamless shopping experience for customers worldwide. By employing AI-powered language translation tools, Ziggany’s can automatically translate product descriptions, reviews, and customer communications into multiple languages, catering to their diverse international clientele.These AI systems, with human review,  can handle the nuances of different languages, maintaining the accuracy and cultural sensitivity of the content. 

Additionally, AI-driven localization algorithms can adapt product content to specific regions, accounting for regional preferences, units of measurement, and currency, providing a tailored and welcoming experience for customers from various cultural backgrounds. This not only expands Ziggany’s global reach but also demonstrates a commitment to inclusivity and customer satisfaction in an increasingly interconnected world.

6. Pair similar products and offer bundles

Pairing similar products and offering bundles is a strategic approach that can significantly boost sales and enhance the customer shopping experience. AI algorithms are instrumental in this process by delving into customer purchase histories and uncovering patterns of products that are frequently bought together.

Imagine a customer browsing Ziggany’s website for a pearl necklace. AI algorithms can analyze data and discover that customers who purchase a pearl necklace often also buy matching pearl earrings or a pearl bracelet to complete the set. Leveraging this knowledge, Ziggany’s can proactively create curated bundles, such as a “Pearl Jewelry Set,” offering a discount for customers who buy all three pieces together.

This approach not only simplifies the shopping process for customers but also encourages them to make larger and more satisfying purchases, increasing both average order value and customer satisfaction.

7. Provide data-driven product recommendations

Enhancing the shopping experience through personalized product recommendations is a powerful strategy that can significantly impact customer satisfaction and sales. AI plays a crucial role in achieving this by meticulously analyzing customer behavior, including browsing habits and past purchase history, to offer tailored product suggestions.

For Ziggany’s, implementing AI-driven personalized recommendations can transform the way customers discover and engage with their jewelry offerings. Imagine a customer who has previously shown a penchant for emerald jewelry. AI algorithms can examine this customer’s browsing and purchase history, identify the preference for emeralds, and then provide personalized suggestions such as emerald necklaces, rings, or earrings.

This level of personalization not only encourages customers to explore a wider range of products but also fosters a deeper connection with the brand, as customers feel understood and valued. In turn, this can lead to higher customer loyalty, increased average order values, and a more enjoyable shopping experience overall.

Embrace the HolidAI Season

As the holiday shopping season dawns upon us, it’s important to recognize the impact that AI will have on the shopping experience this year. Whether you’re using AI technology to introduce new shopping channels, translate detailed product descriptions, or optimize websites for keyword search, this technology has the potential to provide your customers with unparalleled experiences, but only if you have the solid foundation of product information that it requires.

Understanding your customers and adapting to their expectations with the help of AI will be the key to thriving in the holiday rush. Because in 2025, the best gifts brands can give their customers are clarity, convenience, and connection, powered by the smart use of technology.

Black Friday is the biggest endurance test in commerce, where stores are packed, expectations are sky-high, and every detail matters. It’s the one day when even the smallest hiccup can feel magnified under the pressure of crowds. For in-store staff, it’s about staying sharp and being ready to handle the unpredictable pace of the busiest shopping day of the year.

And the stakes are only climbing. In 2024, 81.7 million people shopped in stores on Black Friday, showing just how powerful the in-person retail experience remains. As more customers mix online research with in-store visits, your teams need to deliver trust and reliability on the sales floor. With the right preparation, the rush of Black Friday can transform from an overwhelming challenge into a showcase of your brand at its best. Scroll down below to find out how! 

Top Tips for Preparing In-Store Staff for Black Friday

1. Invest in POS and PIM Systems to Empower Your Staff

A reliable Point-of-Sale (POS) system is the backbone of any successful in-store shopping experience as it can help process transactions quickly and help staff manage promotions under pressure, which is crucial for Black Friday crowds. But even the most advanced POS system can fall short if the product data flowing through it isn’t accurate. Incorrect pricing, incomplete product descriptions, or outdated policies can cause delays and frustration for both employees and shoppers.

That’s where a strong Product Information Management (PIM) solution makes the difference. A PIM system acts as a central hub for managing product data across your entire product catalog. From names and specifications to stock availability, pricing, color and size variations, and related products, a PIM ensures all details are up to date and reflected consistently across sales channels, both digital and physical. When integrated with your POS system and inventory management tools, associates no longer need to guess whether online details match what’s in store because they’ll always have consistent information at their fingertips!

By combining a robust POS system with a reliable PIM solution, like Akeneo PIM, businesses can achieve an enhanced customer experience while ultimately improving shoppers’ trust and loyalty during the busiest shopping season of the year.

2. Introduce AI Checkout to Speed Up Transactions

For many shoppers, the most dreaded part of Black Friday is the line. AI-powered checkout solutions, from smart self-service kiosks to mobile scan-and-go apps, tackle this problem head-on by reducing bottlenecks and shortening wait times. Machine learning algorithms can help to speed up item recognition, flag scanning errors instantly, and even spot fraud patterns, making the checkout process in-store a lot faster and safer. Customers leave with a positive impression, and staff aren’t stuck firefighting at overcrowded registers.

Still, no system is perfect. Hesitant customers or unexpected scenarios will happen, and that’s where trained staff become indispensable. Employees who know how to step in quickly, resolve issues gracefully, and reassure tech-weary shoppers ensure AI feels like a convenience rather than a barrier. By blending high-quality checkout technology with well-prepared staff, retailers can deliver a checkout experience that balances efficiency with human support.

3. Keep Pricing and Policies Aligned Everywhere

Today’s shopper is hyper-informed. They compare prices on their phones while standing in your aisles, and they’ll notice immediately if your online store promises one thing and your physical signage says another. In fact, when it comes to deal days, 62% of shoppers prioritize the lowest price and 59% care most about product quality. 

If those two elements aren’t consistent (and consistently communicated) across channels, customers won’t hesitate to call it out, and your staff will be left in the uncomfortable position of explaining the mismatch! On Black Friday, when the pace is already intense, the last thing employees need is to debate discrepancies with stressed-out shoppers.

That’s why alignment across channels is critical. Policies like shipping cutoffs and return windows should be visible and identical whether a customer is browsing online or in your store. Unified commerce platforms help synchronize all of this data so staff can confidently provide clear answers without hesitation. The goal is to eliminate doubt for both the shopper and the associate.

Tools like Akeneo Activation make this alignment far easier to achieve. By connecting enriched product data directly to leading retailer and marketplace sites, syndication solutions like Akeneo Activation ensure customers see accurate and complete product information no matter where they shop. Channel requirements are automatically updated, reducing the manual effort for teams and giving actionable insights into any mapping or content changes needed. That means fewer errors, less stress for associates on the sales floor, a smoother customer experience, more conversions, and happier staff!

4. Leverage In-Store Staff to Enhance the Hybrid Shopping Experience

Even in a digital-first age, the in-store experience still plays a crucial role in the buying journey, especially with in-person events like Black Friday; nearly half of all consumers plan to shop in-person this upcoming holiday season. 

Click-and-collect orders, ship-to-store pickups, and shoppers who research online but want to see products in person all utilize online touchpoints but ultimately depend on in-store associates to help finalize their decision. Black Friday heightens this hybrid journey, as customers juggle mobile deals and in-person visits to maximize savings.

For staff, this means more than simply fulfilling orders. It means becoming the human bridge between digital research and physical purchase. Associates should be comfortable retrieving online orders quickly, checking inventory across stores, and helping customers compare what they saw online with what’s available in front of them. This fluency across channels reassures customers that they’re making the right decision and makes the shopping journey feel seamless.

Now obviously, in-store staff aren’t magical genies that have the entire product catalog, complete with all variations and stock availability, memorized and ready to go at a moment’s notice. So equipping these teams with the right product information, at the right time, and in the right way is crucial to providing them with the tools they need to properly help customers.

Solutions like Akeneo Shared Catalogs make this even easier. By providing sales teams, retailers and more with on-demand access to current and customized digital product catalogs, Shared Catalogs ensures staff always have the right information at the right time. The portal sets up quickly and syncs with Akeneo PIM, ensuring associates always have up-to-date details. Instead of hunting for specs or prices, staff can focus on building trust and delivering great experiences.

5. Prepare Your Teams and Systems for Cyber Monday’s Surge

Black Friday may feel like the big finish, but Cyber Monday often surpasses it in online volume. The two events are connected, and what happens in-store on Friday directly impacts the following Monday. Returns begin to trickle in over the weekend and questions about online orders spike. If staff aren’t ready, fatigue and disorganization can quickly snowball into missed opportunities.

One smart strategy is to treat Black Friday as a live test for Cyber Monday. Gather quick feedback from associates on what worked and what didn’t, monitor system performance under stress, and identify friction points. Adjustments can be as simple as moving more staff to handle online pickups or updating return signage to reduce confusion.

By Monday, those small but critical improvements can pay off significantly. Customers expect the same speed and consistency whether they’re shopping online or in-store, and the businesses that adjust in real time stand out. 

6. Train Staff to Efficiently Handle Post-Black Friday Returns

The glow of Black Friday fades quickly when returns flood in — and they will. In fact, 69% of consumers have returned a deal-day purchase, most often because of poor product quality, mismatched product images or descriptions, finding a better price late, or simply acting on impulse. 

Returns are a significant part of the post-purchase experience, particularly around the holidays. Customers expect associates to process them quickly and fairly, and a chaotic return process can sour the entire shopping journey. Training staff in return workflows, exceptions, and conflict management helps ensure shoppers leave feeling just as satisfied as they did when they made the purchase.

But returns don’t have to be viewed purely as a loss. With the right mindset and training, they can be reframed as opportunities. Associates who know how to suggest exchanges, upgrades, or loyalty incentives can turn a return into a new sale, and sometimes into a stronger relationship. Instead of seeing returns as a drain on resources, equip staff with the tools and scripts to transform them into moments of retention and even growth!

7. Keep Inventory Accurate and Systems Streamlined

Few things frustrate customers more than being told an item they saw online isn’t actually available in store. Real-time inventory tracking prevents this issue and allows staff to instantly confirm product availability. On Black Friday, when demand is sky-high, this accuracy is critical to keeping customers satisfied and sales flowing.

AI can make this even smarter. AI-driven inventory management can forecast demand patterns and predict low-stock risks in real time. Some solutions go further, offering AI-powered predictive shipping timelines that factor in inventory levels, order location, carrier delays, and even weather conditions. This means in-store staff have access to reliable estimates of stock availability, restock timelines, and shipping estimates if a customer wants a product sent directly to their home, all of which reduces uncertainty and improves confidence.

Systems must also be able to withstand the pressure. If your POS freezes or inventory management lags under peak load, both staff and customers suffer. Frequent updates and contingency planning reduce the risk of breakdowns when the stakes are highest. When employees can trust the data and the systems behind it, they spend less time second-guessing and more time upselling, cross-selling, and enhancing the overall customer experience.

8. Ensure Efficient Supplier Communication

Fast, reliable shipping is no longer just an online concern, but a core part of the in-store promise too. When customers ask about delivery timelines, associates need answers they can trust. Partnering early with shipping providers allows you to anticipate seasonal bottlenecks and communicate realistic delivery expectations.

Clear collaboration with shipping partners is the quiet preparation step that can make or break the post-Black Friday experience. Solutions like Akeneo Supplier Data Manager (SDM) can help ensure efficient communication between suppliers and in-store operations by helping distributors and suppliers streamline product data exchange and enrichment through centralized data collection and collaborative supplier access. This leads to less mistakes, less supply chain friction, and more accurate product data flowing to shipping partners, ensuring deliveries are reliable and margins are protected even during peak holiday demand!

Preparing People, Processes, and Product Content for Black Friday

When customers think of Black Friday they often think of discounts, long lines, and navigating massive crowds in a post-Thanksgiving haze. But when businesses think of Black Friday, they think of all the preparation, organization, and training that goes in to equipping in-store staff with everything they need for one of the busiest shopping weekends of the year.

By utilizing the right technology and the right strategy, retailers can streamline operations while delivering a seamless, trustworthy experience wherever customers are shopping. With the right mix of people, processes, and product content, Black Friday can become a brand-building moment that keeps customers coming back beyond the holiday season.